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Attention Score in Context
Chapter title |
The Use of Temporal Information in Food Image Analysis
|
---|---|
Chapter number | 39 |
Book title |
New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops
|
Published in |
Lecture notes in computer science, August 2015
|
DOI | 10.1007/978-3-319-23222-5_39 |
Pubmed ID | |
Book ISBNs |
978-3-31-923221-8, 978-3-31-923222-5
|
Authors |
Yu Wang, Ye He, Fengqing Zhu, Carol Boushey, Edward Delp, Wang, Yu, He, Ye, Zhu, Fengqing, Boushey, Carol, Delp, Edward |
Abstract |
We have developed a dietary assessment system that uses food images captured by a mobile device. Food identification is a crucial component of our system. Achieving a high classification rates is challenging due to the large number of food categories and variability in food appearance. In this paper, we propose to improve food classification by incorporating temporal information. We employ recursive Bayesian estimation to incrementally learn from a person's eating history. We show an improvement of food classification accuracy by 11% can be achieved. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 12 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 3 | 25% |
Student > Doctoral Student | 2 | 17% |
Student > Bachelor | 2 | 17% |
Student > Ph. D. Student | 2 | 17% |
Professor | 1 | 8% |
Other | 1 | 8% |
Unknown | 1 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 5 | 42% |
Engineering | 2 | 17% |
Nursing and Health Professions | 1 | 8% |
Environmental Science | 1 | 8% |
Medicine and Dentistry | 1 | 8% |
Other | 1 | 8% |
Unknown | 1 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 August 2015.
All research outputs
#15,345,593
of 22,826,360 outputs
Outputs from Lecture notes in computer science
#4,649
of 8,126 outputs
Outputs of similar age
#156,316
of 266,186 outputs
Outputs of similar age from Lecture notes in computer science
#89
of 306 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,186 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 306 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.